The demand for ever cheaper and lighter weight portable electronic devices has led to a growing need to manufacture durable, lightweight, and low cost electronic circuits including high density memory chips. The increasing complexity of electronic devices, and integrated circuits, coupled with the decreasing size of individual circuit elements, places ever more stringent demands on fabrication processes, particularly with respect to the resolution and accuracy of the fabrication patterns. The ability to fabricate on a nanometer scale guarantees a continuation in miniaturization of functional devices.
Micro-fabrication techniques can produce structures having features on the order of nanometers. Micro-fabrication is used in a wide variety of applications, such as the manufacturing of integrated circuits (i.e. semiconductor processing), biotechnology, optical technology, mechanical systems, and micro-electro-mechanical systems (“MEMS”).
Micro-fabrication is typically a multi-step process involving the patterned deposition or removal of material from one or more layers that make up a finished device. Micro-fabrication is sensitive to the presence of contaminant particles. In micro-fabrication it is common to inspect a substrate for the presence of contaminants between process steps. As the size of micro-fabricated features decreases, smaller and smaller contaminant particles and films can affect device yield. A number of tools have been developed for detecting contaminant particles. Inspection tools, such as a scanning electron microscope (SEM) are commonly used to inspect a partially fabricated device or wafer containing multiple devices for defects. For certain cases, it may be sufficient to image the defects, e.g., with the SEM and analyze the image to characterize the defects. But for many cases, once defects have been detected it is important to characterize the material composition.
Instrumentation for use in spectroscopic elemental analysis makes use of electrons, ions, or X-rays which are emitted from a substance after being bombarded or irradiated with electrons or ions from a source such as an electron gun. Energy Dispersive X-ray analysis (EDX) is a technique in which an electron beam strikes the surface of a conducting sample. The energy of the beam is typically in the range 5-20 kilo electron-volts (keV). This causes X-rays to be emitted from the region of impact of the electrons with the sample. The energy of the X-rays emitted depends on the material under examination. For EDX, the X-rays are generated in a region of several hundred nanometers to several microns in depth. For sufficiently large defects, EDX may have adequate sensitivity and spatial resolution. Unfortunately, for very small defects EDX may not have the sensitivity to characterize them.
Another charged particle spectroscopy technique is known as Auger electron spectroscopy (AES). Unlike EDX which detects X-rays, AES detects secondary electrons that are emitted with an energy characteristic of the material of the surface. Auger data is obtained with an electron detection system having an electron energy analyzer, such as a cylindrical mirror analyzer (CMA), hemispherical sector analyzer (HSA), a hyperbolic field analyzer, or an S-curve analyzer.
An example of a hyperbolic field analyzer that may be used to acquire an Auger electron spectrum is disclosed in commonly assigned U.S. Pat. No. 7,635,842 to Mehran Nasser-Ghodsi et al., entitled “METHOD AND INSTRUMENT FOR CHEMICAL DEFECT CHARACTERIZATION IN HIGH VACUUM” filed Feb. 15, 2008, the entire contents of which are herein incorporated by reference.
An example of an S-curve analyzer that may be used to acquire an Auger electron spectrum is disclosed in commonly assigned U.S. Pat. No. 8,421,030 to Khashayar Shadman et al., entitled “CHARGED-PARTICLE ENERGY ANALYZER” filed Mar. 17, 2011, the entire contents of which are herein incorporated by reference.
Acquiring the Auger electron input spectrum with the electron energy analyzer involves bombarding the target sample with a stream of electrons from some source, such as an electron gun, and detecting electron energies emitted therefrom. Upon incidence of the electrons the target material gives off a variety of emissions, including X-rays, secondary electrons, and backscattered primary electrons from the source. The emissions include Auger electrons (a particular class of secondary electrons) in the manner which is well known in the literature. Auger electron spectroscopy is a surface analytical technique because the energies of the electrons emitted are typically in the range of 50 eV to 3 keV, and at this energy they cannot escape from more than a few nanometers deep in the surface (of course, the higher the energy, the thicker the layer from which they can escape).
The emitted electrons are plotted as spectrum that is a function of energy to obtain the input spectrum to be analyzed by the particular Auger electron spectroscopy analytical technique. This input signal includes both a broad background spectrum of secondary electrons as well as one or more Auger spectra for the particular elements present in the target sample. This input spectrum can be analyzed using an appropriate Auger electron spectroscopy analytical technique in order to chemically characterize the target material based on the Auger spectra present in the signal.
Characterizing the surface of the target material may include determining the type of elements present in a spectrum based on the characteristic Auger spectra present in the input spectrum. A general goal of Auger electron spectroscopy analytical technique is to isolate the relevant Auger spectra from the spectral data, which may be a noisy signal that includes both broad background spectrum corresponding to non-Auger secondary electron energies and noise produced by the particular electron detection system used to acquire the data.
However, there are several drawbacks with traditional AES analytical techniques. For one, they suffer from poor performance when attempting to analyze a noisy signal, which may make it difficult to distinguish Auger electron transition peaks in the derivative signal. Moreover, traditional techniques do not handle peak ambiguity well, where different elements and/or chemicals have similar transition peak locations or overlapping Auger spectra in the input spectrum. Additionally, traditional techniques suffer from poor performance with even trivial spectral shifts, such as may be due to chemical composition or calibration issues.
To obtain a good quality signal, i.e. one with a high signal to noise ratio (SNR), the target sample may be placed in an Ultra High Vacuum (UHV), typically about 10−10 Torr to 10−9 Torr. However, the design complexity of UHV systems and slower operational cycle prevents rapid analysis of defects in production-scale substrate processing, which tend to operate at high vacuum, e.g., about 10−7 to about 10−6 torr. Auger spectroscopy can be conducted faster and in a high vacuum environment of a production environment, but the process may produce a lower quality spectral input signal having a low SNR, resulting in poor identification performance when using traditional Auger analytical techniques
It is within this context that aspects of the present disclosure arise.